“Full Strike – using your data to hit targeting, proposition and strategic initiatives with one shot”


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Synopsis: Mobile operators may be overlooking their greatest asset—customer data—as they fight in crowded markets for a competitive edge. To win, they must increase customer spending, reduce churn and attract new subscribers. The vast array of customer data that they generate could be a powerful competitive weapon. However, only when this data is properly gathered, managed and analyzed can its full potential be utilized.

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“Full Strike – using your data to hit targeting, proposition and strategic initiatives with one shot”

  1. 1. Full Strike – using your data to hit targeting, proposition and strategic initiatives with one shot Amit Daniel, EVP Marketing & BD © 2013 – PROPRIETARY AND CONFIDENTIAL INFORMATION OF CVIDYA
  2. 2. The Williams Family 2
  3. 3. Profession Runs his own SME George Devices laptop, tablet, iPhone (paid for by the SME) Patterns uses tethering at work (on the go) and at home Hobbies Football, biking, National Geographic 3 Devices laptop, 2 tablets, Galaxy S3 (paid for by the employer) Naomi Profession EVP Marketing Patterns Voice, SMS, Roaming, WhatsApp, Skype Hobbies Reading, movies, traveling and watching specific series on  TV….
  4. 4. 14 Stella Devices - laptop, tablet, Galaxy S3 Plan - bundle of unlimited SMS and Voice, 1.5GB data (exceeding limit and suffering from bandwidth quality issues) Patterns - Skype, WhatsApp, gaming, HD videos (YouTube) 4 11 Jack Devices - iPhone 4S Plan - bundle of unlimited SMS and Voice, 500MB data Patterns - WhatsApp, Facebook Habits - tennis, basketball, action movies 6 Jane Device - feature phone Plan - prepaid Voice only
  5. 5. • • • • • • • Traveling every 2nd weekend of the month which entails 2-4 hours of driving Traveling abroad – 1-2 times  per  year  (taking  a  few  devices  with  them….) Music concerts – few times per year Attending many family attractions (shows, amusement parks, etc.) Watching movies and purchasing online gaming Usage of Wi-Fi has been reduced Subscribed to broadband and cable TV and VOD Characterizes Them 5
  6. 6. Let’s  Connect  Back  to   The  Provider… Insights  Correlation, relationships, patterns, habits – Data Available XDRs, customer details, device, location, account number, point of sale,  revenues….. 6 – – – Needs and communication habits as a group and as individuals Patterns of use - profile enrichment Influencers Correlations - Friends/family members/SMEs
  7. 7. Analytics is Crucial for Mobile Data Pricing Understanding your data as well as customer usage and needs mean: • Creation of relevant pricing models and campaigns • Innovation  and    “out  of  the  box”  pricing   models with 3rd parties partnerships • “Trial and Error”  mode  of  operation 7
  8. 8. Operators’  Reality “Telcos are sitting on a huge pile of data. But they can only efficiently use a small portion. Leveraging it effectively requires a very targeted approach to  gain  usable  outputs.”   (Deutsche Telekom) “Pricing  models  are  about  moving  from  one-size-fits-all to consumption-based models with much more flexibility and customization built in to allow the end user to make the choices they want to make based on what they need at that moment in time.” (Alicia Dietsch, AT&T) 8
  9. 9. Opportunity loss potential of 230B USD in 2013-2015 Improve CLTV Manage the OTT challenge Maximize returns from LTE Investments 9 Underpin Advanced Segmentation Mobile broadband connections reached $1.6B users in 2012, a 43% growth year-over-year Mobile broadband revenues reached $244.2 billion in 2012, a 21% growth year-on-year Ovum, wireless Intelligence
  10. 10. CMOs’  Challenges   Monetize the vast amount of available customer data, across silos and departments Return the Investment in high-speed networks Maximize revenue from the data growth engine Generate new sources of revenue to compensate for decreasing profitability Offer premium customer experience, to retain competitiveness and market share Quickly and effectively launch new products, tailored  to  customers’  needs  and  preferences Re-structure the product catalog, to align with latest market changes 10
  11. 11. European Telecom Revenues are Decreasing Source: Arthur D. Little, Exane BNP Paribas Note: Countries covered: Germany, France, UK, Italy, Spain, Netherlands, Belgium, Portugal 11
  12. 12. Monetizing Mobile Data Source: ARCEP, Arthur D. Little analysis 12
  13. 13. Tablets Trigger Strong Data Consumption Source: userADgents, Zenith Optimedia, operators, Arthur D. Little analysis 13 Note: 75: of tablets sales would be connected in 2015
  14. 14. Accelerate Data Penetration & Maximize Data Revenue 14
  15. 15. Identify Best Candidates for Data Propositions Find sophisticated combinations of customer profile, device, and usage attributes, which identify customers: 1 2 Who have the highest likelihood for: 3 Whose usage/ ARPU are likely to be impacted most positively by: Whose ARPU is least likely to be cannibalized by: Starting to use data services steadily Upgrading to a more advanced device Increasing volume of data usage Upgrading data bundle  Improving the targeting of data propositions can increase conversion rate by 20-25%.  Focusing on the customers for whom data adoption or upgrade of data bundle is likely to have the most positive impact can increase data revenue per customer by over 10%. 15
  16. 16. Leverage Customer Relations & Influence 1 Reveal related customer groups (families, small businesses), of which all/most members use data services regularly 2 3 Find customers who frequently share their data allowance with additional devices via tethering Identify data users who move their SIM cards between several devices (e.g. smartphone, tablet, modem) Identify best candidates for shared data packs and find their overall data needs Identify Influencers whose profile, usage, device, and price plan make them good candidates for data bundle/ device upgrade 16 Leverage the viral impact of these influencers:  Prioritize the customers in targeting of data bundle upgrade/ device upgrade campaigns  Potentially offer influencers better terms, to ensure their adoption (consider ROI of entire influence group)
  17. 17. Service-Based Data Propositions & 3rd-Party Data Monetization 17
  18. 18. Service-Based Data Propositions Offer customers relevant service-driven, rather than volume driven, data proposition, for premium Quality of Experience and as additional source of data revenue - increase  subscribers’  ARPU  by  3-5 Euros 1 2 3 Customers/ customer groups with highvolume of Facebook/ Twitter usage Customers who are frequently using video streaming/ gaming Customers with highvolume of sports/ music streaming Offer (potentially shared) unlimited Facebook/ Twitter usage, for a fixed monthly fee Offer video optimization service for additional fee, or direct to video optimization guidelines Offer  the  operator’s   sports/ music application, or one promoted by the operator, for a discount 18 4 5 Customers frequently using VoIP on their mobile Customers constantly using data services on an older-generation device Offer guaranteed Quality of Experience for VoIP calls, for an additional fee Offer subsidized upgrade to an advanced device, for better quality of data services, encouraging higher usage
  19. 19. Monetize Mobile App. Downloads & OTT Services Identify  customers’: – Used applications – Areas of interest (sports, gaming, music, videos) – Most used OTT services (e.g. chat applications, VoIP, etc.) Partner with OTT players to improve  customers’  OTT   experience (3rd-party subsidizes extra data volume/ guaranteed QoE) Promote 3rd-party mobile applications most matching customers’  interests Sell device manufacturers statistic data of how their devices are used / Sell app. developers aggregated profiling of their app. users 19 Partner with mobile apps. vendors to sell combined bundles - (data volume + apps.) or (device + apps.) - and split the profits Offer the most popular mobile apps. for free, as a loyalty offer - Get special volume discount from the application vendor
  20. 20. The Williams Family  Offer a shared data plan that covers the needs of all family members , e.g.: – Incentives for gaming / sports providers as part of the pricing bundle – Not  only  mobile…cross  and  up-sell with broadband and VOD offerings 20
  21. 21. What You Should Know - cVidya A leading supplier of Revenue Analytics solutions to communications and digital service providers Founded: 2001 300 employees in 15 locations worldwide Deployed at 7 out of the 10 largest operators in the world 150 customers in 64 countries Globally processing 150 Billion xDRs per day, 55 Trillion xDRs per year Saving over $12 Billion to providers annual revenue Partnering with world leading vendors 21
  22. 22. Turning your DATA into VALUE 22
  23. 23. cVidya  Enrich™  - Product Modules Modular Pre-Modeled Customer Analytics Packages of on-line data analytics, to support strategy of 8 specific business objectives: Accelerate Data Penetration & Increase Data Revenue Service-Based Data Offers & Third-Party Monetization Strategize LTE Migration Optimize Price Plan Mgmt. Improve Customer Retention Improve Customer Acquisition Optimize Pre-paid to Post-paid Migration Optimize Roaming Proposition Advanced Data Analysis - Influencers/ Customer Groups (families, small businesses) Cross-business KPIs - 360° Executive View An included set of always-relevant data analytics 23 Analysis Sandbox Create your own analytical views
  24. 24. THANK YOU! www.cvidya.com